! MPEC formulation for ABS function! y = ABS(x) returns a value y, where:! y = x if the corresponding element of X is greater than zero! y = -x if the corresponding element of X is less than zero! this uses the APMonitor object 'abs'

Mathematical Programs with Equilibrium Constraints (MPECs) are formulations that can be used to model certain classes of discrete events. MPECs can be more efficient than solving mixed integer formulations of the optimization problems.

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Mathematical Programs with Equilibrium Constraints (MPECs) are formulations that can be used to model certain classes of discrete events. MPECs can be more efficient than solving mixed integer formulations of the optimization problems because it avoids the combinatorial difficulties of searching for optimal discrete variables.

Mathematical Programs with Equilibrium Constraints (MPECs) are formulations that can be used to model certain classes of discrete events. MPECs can be more efficient than solving mixed integer problems.

to:

Mathematical Programs with Equilibrium Constraints (MPECs) are formulations that can be used to model certain classes of discrete events. MPECs can be more efficient than solving mixed integer formulations of the optimization problems.

! MPEC formulation for SIGN function! y = SIGN(x) returns a value y, where:! 1 if the corresponding element of X is greater than zero! -1 if the corresponding element of X is less than zeroModel signum Parameters x = -2 End Parameters

Mathematical Programs with Equilibrium Constraints (MPECs) are formulations that can be used to model certain classes of discrete events. MPECs can be more efficient than solving mixed integer problems.